This invention relates generally to the reception and decoding of digitally modulated radio signals and, in particular, to a detection and decoding algorithm which provides a sub-optimal solution for an equalizer and symbol detector that approximates the performance of an optimal equalizer and an optional symbol detector but considerably reduces computational load.
There has been an exponential increase in demand for wireless communication devices which was initiated by the development of cellular telephones. Recently, many applications have been developed which use wireless devices for transmitting digital data. Those applications include communications services such as electronic mail and text paging, wireless World Wide Web access, wireless file transfer, etc. The use of digitally modulated radio signals for data transfer has generated a demand for faster transfer rates. An accepted method of increasing digitally modulated radio signal transfer rates is to use multiple-phase-shift-keying (MPSK) as the modulation scheme. With MPSK, complexity becomes an important issue in the development of a receiver. As is well understood, as the number of points in an MPSK constellation increases, there is a corresponding increase in the sensitivity to additive white gaussian noise (AWGN) which cannot be avoided.
Digitally modulated radio signals also are subject to degraded signal quality as a result of multipath fading caused by environmental factors such as terrestrial terrain, co-channel interference and noise corruption. Multipath fading and Doppler effects caused by mobile channels causes intersymbol interference (ISI) which can have very undesirable results on performance during data transfer. In extreme cases, a bit-error rate (BER) can reach levels that are outside the limitations specified for acceptable or useful communications.
An equalizer structure is required to compensate for the ISI caused by dispersion resulting from multipath fading and Doppler effects. As is well understood in the art, there is a window associated with equalization. The length of the window determines how well an equalizer works. The longer the window, the greater the number of ISI terms that the equalizer is able to compensate. However, the longer the window, the greater the complexity of the processing required. In general, the number of states that must be considered for an ISI term is ML where M is the number of points in an MPSK constellation and L is the length of the equalization window. Consequently, computational load rapidly increases as points are added to an MPSK constellation.
It is well known in the art that an optimal equalizer can be constructed using a maximum-likelihood sequence-estimation (MLSE) structure utilizing the well known Viterbi algorithm. However, the complexity of the Viterbi algorithm grows exponentially with the number of states required in processing. The exponential increase in the number of states required in processing makes the MLSE structure impossible to implement at reasonable cost in a real radio receiver using known technology.
Alternatives to the MLSE structure have been developed. One alternative known as the minimum-mean-squared-error (MMSE) structure, such as a decision-feedback equalizer (DFE), is known to be simpler to implement. However, its performance can be quite poor for high density MPSK constellations, and consequently it has proven to be unacceptable for mobile radio data communications applications which use high density MPSK.
In order to provide a near optimal equalizer which can be implemented in radio receivers, a sub-optimal structure that provides performance superior to the MMSE structure and yet significantly reduces the computational load of the equalization process has been invented. This structure is described in co-pending PCT Application Serial No. PCT/FR99/00661, which designates the United States and is entitled A METHOD OF NUMERICAL EQUALIZATION AND WIRELESS RECEPTION EMPLOYING SUCH A METHOD which was filed on Mar. 25, 1998 by Applicants"" subsidiary Nortel Matra Cellular. This equalizer structure provides a sub-optimal solution which approximates the performance of the MLSE structure while considerably reducing computational intensity.
However, as the demand for faster and more efficient wireless data communications increases, there is a need for a radio signal equalizer capable of better performance while requiring less computational intensity, so that the reliability of data transfer is improved while the cost of radio transceivers is reduced.
Furthermore, prior art radio frequency receiver models segregate equalization from symbol detection. Equalization is performed first and then symbol detection is performed. This limits the computational time available for both equalization and symbol detection. There therefore exists a need for an algorithm that enables simultaneous equalization and symbol detection for MPSK digitally modulated radio signals.
It is therefore an object of the invention to provide a radio signal equalizer and an MPSK symbol detector capable of improved performance while requiring fewer computations than MPSK symbol detectors known in the prior art.
Accordingly, an aspect of the present invention provides a method of detecting data symbols of an MPSK modulated slot received by a radio receiver. The method includes a first step of preparing an initial solution vector, including an estimated value for each data symbol. A solution error of the solution vector is then calculated, and the solution error is minimized by perturbating the solution vector.
A further aspect of the invention provides an equalizer and data symbol detector for MPSK modulated slots received by a radio receiver. The equalizer and data symbol detector comprises a processor adapted to prepare an initial solution vector including an estimated value for each data symbol. The processor subsequently calculates a solution error for the solution vector, and minimizes the solution error by perturbating individual data values of the solution vector in a systematic way.
A still further aspect of the present invention provides a radio communications device adapted for radio communication of data symbols of an MPSK modulated slot. A receiver is adapted to receive a radio signal containing the MPSK modulated slot. A sampler is adapted to sample the received radio signal to generate a sample vector of the received slot. Finally, a processor is adapted to compute an initial solution vector including an estimated value for each data symbol. The processor then calculates a solution error for the solution vector, and minimizes the solution error by perturbating individual data values of the solution vector in a systematic way.
In accordance with the invention, the initial solution vector is prepared by estimating a value for each data symbol of the solution vector by single-symbol detection.
In an embodiment of the invention the steps of calculating a solution error and minimizing the solution error are repeated recursively until a predetermined terminating condition is satisfied. The predetermined terminating conditions may include the solution error being less than a predetermined threshold value, a change in the solution error between successive iterations less than a predetermined threshold value, or a number of iterations performed equals a predetermined number.
In an embodiment of the invention, perturbation of the solution vector comprises successively perturbating the value of only one symbol of the solution vector and computing a solution error after each perturbation. Preferably, perturbating the value of each symbol of the solution vector is done by substituting an initial value d[n]0 of the symbol with a first neighboring value from an MPSK constellation d[n]0+1. A solution error xcex50+1 for the solution vector modified by the substitution of the first neighboring value is then computed. The initial value d[n]0 of the symbol is then substituted with an opposite neighboring value from the MPSK constellation d[n]0xe2x88x921. A respective second solution error xcex50xe2x88x921, for the solution vector including the second neighboring value is computed. The three solution errors, xcex50, xcex50+1 and xcex50xe2x88x921, are then compared and the smallest solution error is selected. If the smallest solution error is not xcex50, the neighboring value corresponding to the smallest solution error is adopted as the value of d[n].
Preferably, the value of only one symbol is perturbated during each perturbation step.
Preferably, the value of each symbol of the solution vector is perturbated in an order opposite to an order of estimation of values of the initial solution vector.